Jean-Paul Arcangeli

Université Toulouse - Jean Jaurès

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Sébastien Leriche

École Nationale de l’Aviation Civile

Françoise Adreit

Université Toulouse - Jean Jaurès

Sylvie Trouilhet

Institut de Recherche en Informatique de Toulouse

Sylvie Trouilhet

Université Toulouse III - Paul Sabatier

Victor Noël

Institut Agro Rennes-Angers

W. Younes

Lawrence Livermore National Laboratory

Thierry Desprats

Institut de Recherche en Informatique de Toulouse

Chantal Taconet

Telecom SudParis

Frédéric Migeon

Université Toulouse - Jean Jaurès

Jean‐Michel Bruel

Université Toulouse III - Paul Sabatier

Cooperative Institutions

Université Toulouse III - Paul Sabatier

Institut de Recherche en Informatique de Toulouse

Université Toulouse - Jean Jaurès

Université de Toulouse

Centre National de la Recherche Scientifique

Université Toulouse-I-Capitole

Institut Polytechnique de Bordeaux

Orange (France)

Telecom SudParis

Institut National Polytechnique de Toulouse

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Impact assessment modeling of low-water management policy

HAL (Le Centre pour la Communication Scientifique Directe) (2013)

Pierre Mazzéga Christophe Sibertin‐Blanc Olivier Thérond Frédéric Amblard Jean-Paul Arcangeli

We briefly present the main steps involved in designing and developing a platform for the numerical simulation of environmental and social impacts of the implementation of new environmental norms related to low-water management in France (MAELIA Project: multi-agents for environmental norms impact assessment). Some results are highlighted concerning in particular the structure of the underlying low-water management model and the process and agents' activity modeling.

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Model-Driven Engineering for End-Users in the Loop in Smart Ambient Systems

JUCS - Journal of Universal Computer Science (2021)

Sylvie Trouilhet Jean-Paul Arcangeli Jean‐Michel Bruel Maroun Koussaifi

At the heart of cyber-physical and ambient systems, the user should permanently benefit from applications adapted to the situation and her/his needs. To do this, she/he must be able to configure her/his software environment and be supported as much as possible in that task. To this end, an intelligent “engine” assembles software components that are present in the ambient environment at the time and makes unanticipated applications emerge. The problem is to put the user “in the loop”, i.e., provide adapted and intelligible descriptions of the emerging applications, and present them so that the user can accept, modify or reject them. Besides, user feedback must be collected to feed the engine’s learning process. Our approach relies on Model-Driven Engineering (MDE). However, differently from the regular use of MDE tools and techniques by engineers to develop software and generate code, our focus is on end-users. Models of component assemblies are represented and made editable for them. Based on a metamodel that supports modeling and de- scription of component-based applications, a user interface provides multi-faceted representations of the emerging applications and captures user feedback. Our solution relies on several domain- specific languages and a transformation process, based on the established MDE tools (Gemoc studio, Eclipse Modeling Framework, EcoreTools, Sirius, Acceleo). It works in conjunction with the intelligent engine that builds the emerging applications and to which it provides learning data.

Model-driven architecture

Component (thermodynamics)

Metamodeling

Eclipse

Model Transformation

Interface (matter)

10.3897/jucs.70515

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Automatic testing of OCE, a human-centered reinforcement learning system for automated software composition

HAL (Le Centre pour la Communication Scientifique Directe) (2022)

Maxence Demougeot Kévin Delcourt Jean-Paul Arcangeli Sylvie Trouilhet Françoise Adreit

Software testing

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Mission-Aware Adaptive Communication for Collaborative Mobile Entities

IGI Global eBooks (2011)

Jérôme Lacouture Ismael Bouassida Rodriguez Jean-Paul Arcangeli Christophe Chassot Thierry Desprats

Adaptation of communication is needed to maintain the connectivity and quality of communication in group-wide collaborative activities. This becomes quite a challenge to handle when mobile entities are part of a wireless environment, in which responsiveness and availability of the communication system are required. In this chapter, these challenges are addressed within the context of the ROSACE project where mobile ground and flying robots have to collaborate either between them selves or with remote artificial and human actors during save and rescue missions in the event of disasters such as forest fires. This chapter presents our first results. The final goal is to propose new concepts, models and architectures that supports cooperative adaptation which is aware of the mission being executed. Thus, the communication system can be adequately adapted in response to predictable or unpredictable evolutions of the activity requirements and to the unpredictable changes in the communication resource constraints.

Unexpected events

10.4018/978-1-60960-042-6.ch064

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Opportunistic Composition of Human-Computer Interactions in Ambiant Spaces

Augustin Degas Jean-Paul Arcangeli Sylvie Trouilhet Gaëlle Calvary Joëlle Coutaz

We propose an approach based on Adaptive Multi-Agent Systems, using the principles of Meta-User Interfaces and Opportunism in order to solve Human-Computer Interaction Composition in Ambient interactive spaces. The idea of this approach is to see every component as an agent able to interact with other components to compose autonomously in order to opportunistically suggest to users smart compositions of his interactive ambient environment. We present the notions of component, composition, and human-computer interaction composition. We chose mainly two aspects of the composition of human-computer interaction which are the controllability and finality of the composition. Finally, we illustrate our approach with use cases taken from the neoCampus project.

Component (thermodynamics)

Ambient Intelligence

10.1109/uic-atc-scalcom-cbdcom-iop-smartworld.2016.0156

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Scenario-based Automatic Testing of a Machine Learning Solution with the Human in the Loop

Maxence Demougeot Sylvie Trouilhet Jean-Paul Arcangeli Françoise Adreit

Human-in-the-loop

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Quality-Based Reinforcement Learning in Intelligent Opportunistic Software Composition

Kahina Hacid Sylvie Trouilhet Françoise Adreit Jean-Paul Arcangeli

Internet of Things and cyber-physical systems are characterised by openness and an increasing number of devices and their associated services. In a previous work, we have proposed to exploit opportunistically these services in order to automatically make emerge customised applications that suit user preferences. For that, we have developed a generic solution for bottom-up opportunistic service composition, based on reinforcement learning. In this work, it is extended to handle more efficiently the appearance of new components using service annotation and quality attributes in order to generalise and share knowledge with new discovered services. A didactic use case is used for illustration and demonstration purposes.

Openness to experience

10.1109/wetice53228.2021.00013

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Engineering Agent Frameworks: An Application in Multi-Robot Systems

Advances in intelligent and soft computing (2011)

Jérôme Lacouture Victor Noël Jean-Paul Arcangeli Marie-Pierre Gleizes

Component (thermodynamics)

Relevance

10.1007/978-3-642-19875-5_10

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Citations (4)

Adaptive Autonomous Agent Models for Open Distributed Systems

Sébastien Leriche Jean-Paul Arcangeli

Currently, there is a lack of tools to build autonomous software systems in a pervasive and distributed context. In this paper, we present a model and a development tool called Agent ^phi for building flexible agent architectures from fine-grained components. Reusable components implement non-functional mechanisms such as communication, mobility or adaptation skills. Each agent can dynamically and autonomously change its components to suit its runtime context, improving safety and performances of applications, particularly in open, pervasive or large-scale distributed applications. We also show how to use our agents to build applications from autonomous and adaptable systems.

Autonomous agent

Software agent

10.1109/iccgi.2007.10

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Citations (7)

Between Design and Implementation of Multi-Agent Systems: A Component-Based Two-Step Process

HAL (Le Centre pour la Communication Scientifique Directe) (2010)

Victor Noël Jean-Paul Arcangeli Marie-Pierre Gleizes

Component (thermodynamics)

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